18 citations · 68 across the 16 of their papers we have counts for
6 papers · 1 filter
Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search
Man Luo, Bowen Du, Konstantin Klemmer +2
Shared e-mobility services have been widely tested and piloted in cities across the globe, and already woven into the fabric of modern urban planning. This paper studies a practica…
Positional Encoder Graph Neural Networks for Geographic Data
Konstantin Klemmer, Nathan Safir, Daniel B. Neill
Graph neural networks (GNNs) provide a powerful and scalable solution for modeling continuous spatial data. However, they often rely on Euclidean distances to construct the input g…
SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss
Konstantin Klemmer, Tianlin Xu, Beatrice Acciaio +1
From ecology to atmospheric sciences, many academic disciplines deal with data characterized by intricate spatio-temporal complexities, the modeling of which often requires special…
Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Gyri Reiersen, David Dao, Björn Lütjens +3
Forest carbon offsets are increasingly popular and can play a significant role in financing climate mitigation, forest conservation, and reforestation. Measuring how much carbon is…
Generative modeling of spatio-temporal weather patterns with extreme event conditioning
Konstantin Klemmer, Sudipan Saha, Matthias Kahl +2
Deep generative models are increasingly used to gain insights in the geospatial data domain, e.g., for climate data. However, most existing approaches work with temporal snapshots…
Proceedings of the NeurIPS 2020 Workshop on Machine Learning for the Developing World: Improving Resilience
Tejumade Afonja, Konstantin Klemmer, Aya Salama +3
These are the proceedings of the 4th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fourth Conference on Neural Information Processing Sys…